Managerial Statistics Syllabus

International Academy of Management and Economics Noli Santos International Tower, 1061 Metropolitan Ave. San Antonio Village Makati City, Philippines

MASTER IN BUSINESS ADMINISTRATION CDI-SAKATA MBA PROGRAM

COURSE SYLLABUS BUS 576: Managerial Statistics

Professor: Pedrito A. Salvador E-mail Address: [email protected] [email protected] Cell No. 63 09173882477

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COURSE DESCRIPTION The Managerial Statistics Course will focus on statistical decision making in today's dynamic business environment where products and processes are continuously improving. Decisions by modern managers are increasingly data driven and require a range of statistical skills including, gathering and describing data, designing samples and experiments, drawing statistical inferences and conclusions, evaluating the confidence of conclusions, developing regression models for anticipating future behavior and use of statistical quality control and six sigma to drive process improvement. All of these important capabilities must be utilized by a manager to make informed decisions. This course will be taught in six major modules, representing each of the skills a business manager must master. Readings will be assigned for each module and homework problems plus case studies will be assigned for analysis and class discussion. The case studies will use actual business examples to aid understanding of the statistical principles and assist translation to actual use. Extensive use will be made of the Minitab computer program for representing and analyzing data. COURSE OBJECTIVES The course is designed with the following objectives in mind: 1. Students should gain a thorough overview of the statistical skills required for today’s managers. 2. Students should obtain an understanding of certain statistical best practices that should assist them in making informed business decisions. 3. Students should develop the framework for making data driven process improvements in technology based organizations. REQUIRED TEXT & COMPUTER PROGRAM 1) Ken Black, Business Statistics for Contemporary Decision Making, Fourth Edition, 2004, John Wiley & Sons, ISBN: 047142983X.

2) Minitab Computer Program Release 13

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COURSE OUTLINE The following major topics will be covered by the course. PowerPoint presentation will typically be assigned on each group from the required text. Exercises from the text and a case study will be assigned as homework and will be submitted during the topic presentation. Assigned group should be prepared to discuss their analysis of the exercises and case study during the class. The class will discuss the results and provide additional recommendations or feedback on the analysis. Introduction (4 weeks) Topics covered include an introduction to statistics, charts and graphs for describing data, standard terms for representing data and a review of probability. Data Distributions (3 weeks) Topics include discrete and continuous distributions of data, use of sampling and understanding sampling distributions. Statistical Inference (3 weeks) Topics include making statistical inferences for populations of data, establishing confidence intervals and conducting hypothesis testing. Variance Analysis and Design of Experiments (1 week) Topics include analysis of the variance of data and statistical approaches to designing experiments. Regression Analysis (2 weeks) Topics include simple and multiple regression analysis, developing regression models and forecasting future data trends. Statistical Quality Control (2 weeks) Topics include statistical process control, process analysis, and six sigma. COURSE DELIVERABLES Homework problems and case study results - Students will be assigned textbook reading, exercises and analysis of a case study as part of a weekly homework assignment. Students should submit their homework and assigned group to present their findings and analysis during the class presentation.

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Quizzes - A short quiz will be conducted following each class. The quiz will emphasize major themes of the lecture and will assist the instructor in verifying that key course material is being adequately conveyed. Midterm Exam - A midterm exam will be conducted for the class. It will emphasize the major themes of the entire course to that point and will indicate the student's assimilation of the course material covered. Final Project - The final project will be an assessment by the student of an existing manufacturing or service based organization or firm. In the assessment the student will utilize the statistical tools covered in the course to either analyze a current process of the firm or recommend suggested improvements that may enhance productivity or to analyze an technical or marketing issue in which the firm needs to make a business decision. Results of the final project will be presented to the class. Criteria for evaluation of the final project presentation are included further on in this document. COURSE GRADING The course grade will be computed from the following components: 1. Theory PowerPoint Presentation 15% 2. Case Study Analyses/Presentation 20% 3. Homework and Quizzes 20% 4. Midterm Exam 20% 5. Final Project 25%

Final Project Presentation Evaluation Form The group presentation to will be evaluated based on its content and quality. Each of these categories will be evaluated using the following criteria: I. Content (75%) A. Presentation of Objective (5%) B. Definition of Current Process or Issue (15%) C. Use of Statistical Tools (10%) D. Recommended Improvements (10%)

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E. Analysis of Recommendations (15%) F. Expected Benefits (10%) G. Analysis of Potential Risks (10%) II. Quality (25%) A. Organization of Presentation (10%) B. Method(s) of Presenting Information (5%) C. Overall Impression (10%)

COURSE WEEKLY SCHEDULE Session

Topics

Session 1-Class Organization

Responsibility Professor

-Introduction to Statistics Session 2 - Descriptive Charts and Graphs

Professor

Session 3 - Descriptive Statistics

Professor

Session 4 – Probability

Group 1

Case: Session 5 - Discrete Distributions -

Group 2

Continuous Distributions Case:

Session 6 - Sampling and Sampling Distributions

Group 3

Case: Session 7 - Statistical Inference

Group 4

Case:

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Session 8- Mid-Term Examination

All Students

Session 9 - Hypothesis Testing for Single Populations

Group 1

Case: Session 10 - Statistical Inference about Two Populations

Group 2

Case: Session 11 - Analysis of Variance and Design of Experiments

Group 3

Case: Session 12 - Simple Regression Analysis -

Group 4

Multiple Regression Analysis Case:

Session 13 – Forecasting

Professor

Session 14 – Statistical Quality Control

Professor

Session 15 - Final Examination

All Students

End

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